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Titlebook: Computational Science – ICCS 2020; 20th International C Valeria V. Krzhizhanovskaya,Gábor Závodszky,Jo?o T Conference proceedings 2020 Spri

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樓主: Buchanan
41#
發(fā)表于 2025-3-28 17:00:19 | 只看該作者
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發(fā)表于 2025-3-29 01:53:19 | 只看該作者
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發(fā)表于 2025-3-29 04:40:05 | 只看該作者
Analytical Techniques for the Identification of a Musical Score: The Musical DNAs regards knowing how to manage the information contained in a document in order to extract its content and interpret it. On the one hand due to the heterogeneity of the information contained on the web (text, image, video, musical scores), and on the other hand to satisfy the user who generally sea
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發(fā)表于 2025-3-29 10:47:42 | 只看該作者
Reduced-Cost Constrained Modeling of Microwave and Antenna Components: Recent Advances particular, multiple simulations entailed by parametric optimization or uncertainty quantification may considerably slow down the design processes. In order to address this problem, it is possible to employ fast metamodels. Here, the popular solution approaches are approximation surrogates, which a
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發(fā)表于 2025-3-29 12:24:06 | 只看該作者
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發(fā)表于 2025-3-29 17:04:04 | 只看該作者
Model-Based Sensitivity Analysis of?Nondestructive Testing Systems Using?Machine Learning Algorithms this work, neural networks (NN) and convolutional NN (CNN) are shown to be computationally efficient at making model prediction for NDT systems, when compared to models such as polynomial chaos expansions, Kriging and polynomial chaos Kriging (PC-Kriging). Three different ultrasonic benchmark cases
48#
發(fā)表于 2025-3-29 22:32:29 | 只看該作者
Application of Underdetermined Differential Algebraic Equations to Solving One Problem from Heat Masry differential equations, algebraic relations and a single partial differential equation, which, written together, can be viewed as an underdetermined differential algebraic equation with a partial differential equation attached. Using the tools of the differential algebraic equation theory, we rev
49#
發(fā)表于 2025-3-30 03:33:25 | 只看該作者
Fully-Asynchronous Fully-Implicit Variable-Order Variable-Timestep Simulation of Neural Networkson intervals, with parallel neurons interpolation and collective communication guiding synchronization. Such simulations, driven by stiff dynamics or wide range of time scales, struggle with fixed step interpolation methods, yielding excessive computation on intervals of quasi-constant activity and
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發(fā)表于 2025-3-30 04:16:38 | 只看該作者
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